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Big Data

Businesses today operate on the monitor-mine-manage (M3) cycle: they monitor and archive large amounts of data, which they mine to derive insights such as models. The models are used during the manage phase to add value to the business, e.g., by scoring the models with real-time data. This project looks at the broad area of platforms and applications for big data analytics, from a database-oriented perspective, in the context of achieving a frictionless M3 cycle.

  • Badrish Chandramouli, Jonathan Goldstein, and Songyun Duan, Temporal Analytics on Big Data for Web Advertising, in 28th International Conference on Data Engineering (ICDE '12), IEEE, April 2012.
  • Badrish Chandramouli, Justin J. Levandoski, Ahmed Eldawy, and Mohamed Mokbel, StreamRec: A Real-Time Recommender System, in ACM SIGMOD International Conference on Management of Data (SIGMOD 2011), ACM SIGMOD, June 2011.
  • Badrish Chandramouli, Mohamed Ali, Jonathan Goldstein, Beysim Sezgin, and Balan S. Raman, Data Stream Management Systems for Computational Finance, in IEEE Computer, IEEE Computer Society, December 2010.
  • Mohamed Ali, Ciprian Gerea, Balan S. Raman, Beysim Sezgin, Tiho Tarnavski, Tomer Verona, Ping Wang, Peter Zabback, Anton Kirilov, Asvin Ananthanarayan, Ming Lu, Alex Raizman, Ramkumar Krishnan, Roman Schindlauer, Torsten Grabs, Sharon Bjeletich, Badrish Chandramouli, Jonathan Goldstein, Sudin Bhat, Ying Li, Vincenzo Di Nicola, Xianfang Wang, David Maier, Ivo Santos, Olivier Nano, and Stephan Grell, Microsoft CEP Server and Online Behavioral Targeting, in International Conference on Very Large Data Bases (VLDB), Lyon, France, August 2009.
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